Abstract
The Social Internet of Things (SIoT) is a combination of the Internet of Things (IoT) and social networks, which enables better service discovery and improves the user experience. The threat posed by the malicious behavior of social network accounts also affects the SIoT, this paper studies the analysis and prediction of malicious behavior for SIoT accounts, proposed a method for predicting malicious behavior of SIoT accounts based on threat intelligence. The method uses support vector machine (SVM) to obtain threat intelligence related to malicious behavior of target accounts, analyze contextual data in threat intelligence to predict the behavior of malicious accounts. By collecting and analyzing the data in a SIoT environment, verifies the malicious behavior prediction method of SIoT account proposed in this paper.
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Acknowledgements
This research was supported by the National Natural Science Foundation of China (61672206,61572170), Hebei Province Science and Technology Support Program (17210104D), Hebei Province Innovation Capacity Improvement Program Soft Science Research and Science Popularization Project (17K50702D), College Science and Technology Research Project of Heibei Province (ZD2015099). Yuzi Yi is the corresponding author of this article.
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Zhang, H., Yi, Y., Wang, J. et al. Network attack prediction method based on threat intelligence for IoT. Multimed Tools Appl 78, 30257–30270 (2019). https://doi.org/10.1007/s11042-018-7005-2
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DOI: https://doi.org/10.1007/s11042-018-7005-2